def draw_around_box(image: OrthographicImage,
box: Dict[str, List[float]],
draw_lines=False) -> None:
bin_border = get_rect(size=box['size'], center=box['center'])
image_border = get_rect(size=[10.0, 10.0, box['size'][2]])
image_pose = Affine(image.pose.x, image.pose.y, -image.pose.z,
image.pose.a, image.pose.b, image.pose.c)
bin_border_projection = [image.project(image_pose * p) for p in bin_border]
color = [
max(
image.value_from_depth((image_pose * border.inverse()).z)
for border in bin_border)
] * 3
if draw_lines:
color_direction = (0, 255 * 255, 0) # Green
for i in range(len(bin_border)):
cv2.line(image.mat, tuple(bin_border_projection[i]),
tuple(bin_border_projection[(i + 1) % len(bin_border)]),
color_direction, 1)
else:
image_border_projection = [
image.project(image_pose * p) for p in image_border
]
cv2.fillPoly(
image.mat,
np.array([image_border_projection, bin_border_projection]), color)
def draw_around_box(image: OrthographicImage, box: Dict[str, List[float]], draw_lines=False) -> None:
bin_border = get_rect(size=box['size'], center=box['center'])
image_border = get_rect(size=[10.0, 10.0, box['size'][2]])
image_pose = Affine(image.pose)
color_divisor = 255 * 255 if image.mat.dtype == np.float32 else 1
bin_border_projection = [image.project((image_pose * p).to_array()) for p in bin_border]
if draw_lines:
color_direction = np.array([0, 255 * 255, 0]) / color_divisor # Green
for i in range(len(bin_border)):
cv2.line(
image.mat, tuple(bin_border_projection[i]),
tuple(bin_border_projection[(i + 1) % len(bin_border)]),
color_direction, 1
)
else:
color = np.array([
max(image.value_from_depth((image_pose * border.inverse()).z) for border in bin_border)
] * 3) / color_divisor
image_border_projection = [image.project((image_pose * p).to_array()) for p in image_border]
cv2.fillPoly(image.mat, np.array([image_border_projection, bin_border_projection]), color)
def get_images(self, image: OrthographicImage):
root = tk.Tk()
image_array = Image.fromarray(cv2.merge(cv2.split(image.mat)))
image_gtk = ImageTk.PhotoImage(image=image_array)
load_new_image = False
ann = [-1000, -1000]
def mouse_clicked(event):
x, y = event.x, event.y
ann[0] = x - self.size_input[0] / 2
ann[1] = y - self.size_input[1] / 2
image_show = Image.fromarray(cv2.merge(cv2.split(image.mat)))
cv2.circle(image_show, (x, y), 2, (255, 255, 255), -1)
image_array = Image.fromarray(cv2.merge(cv2.split(image_show)))
image_gtk = ImageTk.PhotoImage(image=image_array)
panel.configure(image=image_gtk)
panel.image = image_gtk
def button_submit():
root.destroy()
def new_image():
load_new_image = True
root.destroy()
panel = tk.Label(root, image=image_gtk)
button = tk.Button(root, text='Grasp Object', command=button_submit)
button2 = tk.Button(root, text='New Image', command=new_image)
panel.pack(side='top')
button.pack(side='bottom')
button2.pack(side='bottom')
panel.bind('<Button 1>', mouse_clicked)
root.mainloop()
if load_new_image:
return Action()
draw_around_box(image, box=self.box)
background_color = image.value_from_depth(-(image.pose * Affine(0, 0, self.box['size'][2])).z)
image_resized = cv2.resize(image, self.size_resized)
images = []
anns = []
for a in self.a_space:
rot_mat = cv2.getRotationMatrix2D(
(self.size_resized[0] / 2, self.size_resized[1] / 2),
a * 180.0 / np.pi,
1.0,
)
rot_mat[:, 2] += [
(self.size_rotated[0] - self.size_resized[0]) / 2,
(self.size_rotated[1] - self.size_resized[1]) / 2,
]
dst_depth = cv2.warpAffine(image_resized, rot_mat, self.size_rotated, borderValue=background_color)
images.append(crop(dst_depth, self.size_cropped))
ann_scaled = (float(ann[0]) / self.scale_factors[0], float(ann[1]) / self.scale_factors[1])
ann_scaled_rot = self.rotate_vector(ann_scaled, a)
ann_scaled_rot_pos = (
int(round(ann_scaled_rot[0] + self.size_cropped[0] / 2)),
int(round(ann_scaled_rot[1] + self.size_cropped[1] / 2)),
)
x_vec = np.zeros(self.size_cropped[0])
y_vec = np.zeros(self.size_cropped[1])
if 0 <= ann_scaled_rot_pos[0] < self.size_cropped[0]:
np.put(x_vec, ann_scaled_rot_pos[0], 1)
if 0 <= ann_scaled_rot_pos[1] < self.size_cropped[1]:
np.put(y_vec, ann_scaled_rot_pos[1], 1)
ann_matrix = 255 * np.outer(y_vec, x_vec)
anns.append(ann_matrix)
return images, anns